The scavenging of volatile anesthetic agents in the cardiovascular intensive care unit environment: a technical report La recuperation des agents anesthesiques volatils dans l'environnement de l'unitedes soins intensifs cardiovasculaires: un rapport technique
Bibliographic record
Abstract
Purpose The use of volatile-based sedation within critical care environments has been limited by difficulties of drug administration and safety concerns over environment pollution and staff exposure in an intensive care unit (ICU) with no scavenging. The aim of this study was to develop a simple scavenging system to be used with the Anesthesia Conserving Device (AnaConDa) and to determine whether or not ambient concentrations of residual anesthetic are within current acceptable limits. Technical features The scavenging system consists of two Deltasorb canisters attached to the ICU ventilator in series. AnaConDa is a miniature vaporizer designed to provide volatile-based sedation within an ICU. The first ten patients recruited into a larger randomized trial assessing outcomes after elective coronary graft bypass surgery were sedated within the cardiac ICU using either isoflurane or sevoflurane. Sedation was guided by the Sedation Agitation Scale, resulting in an end-tidal minimum anesthetic concentration of volatile agent ranging from 0.1-0.3. At one hour post ICU admission, infrared photometric analysis was used to assess environmental contamination at four points along the ventilator circuit and scavenging system and around the patient’s head. All measurements taken within the patient’s room were below 1 part per million, which satisfies criteria for occupational exposure. Conclusions This study shows that volatile agents can be administered safely within critical care settings using a simple scavenging system. Our scavenging system used in conjunction with the AnaConDa device reduced the concentration of environmental contamination to a level that is acceptable to Canadian standards and standards in most Western countries and thus conforms to international safety standards. The related clinical trial was registered at www.clinicaltrials.gov (NCT01151254).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".